Resume

Short resume :

2012-now

“Habilitation à Diriger des Recherches” at ParisV - CR1

Since Nov. 2008

CNRS researcher in LIMMS/CNRS-IIS, UMI2820 Tokyo : Unconventional computing using microfluidic/biochemical hybrid structures This project is at the interface between system chemistry, reaction diffusion system and amorphous computing. The goal is to create a tool box of simple chemical reactions that can be easily wired together in order to obtain networks. Like in electronics these networks are able to perform high level functions like information processing, control or sensing.

May 2008

CCRIM consultant. Problem solving, scientific and TRIZ expertise.

April 2002

Post-doc in Nanotech for Biophysics. University of Tokyo. Pr. Noji’s group | “Microchambers for the study of mechanically driven ATP synthesis by F1 protein motor.” The goal was to detect the tiny amount of ATP produced from ADP by a single nanometric F1 motor under forced rotation.

1- Artificial reaction networks for the design of in vitro dynamics

Context :

Living organisms are chemical objects, but they are fundamentally different from man-made chemistry. This is because living organisms are organized in systems (networks) of chemical transformations and because they process information rather that matter. Another point in that they are evolved rather than designed. We have reported a method to build artificial circuits that mimic biological systems and are now exploring the design process. We target out-of-equilibrium temporal and spatio-temporal (reaction-diffusion) systems, collective behaviours of particles and stochastic dynamics in micro-compartments.

We use DNA amplification reactions to create simple modules, like activation, inhibition or degradation. Then, we use computer assisted design tools1 to guide the experiments toward the realization of a particular function.

Results :

This learning-by-doing approach gives insights about biological networks and provide useful information concerning their design rules2. On the way to artificial morphogenesis, we have recently shown spatiotemporal behaviors3, and compartmentalized molecular programs4.

Chemical communication in a population of DNA-programmed microscopic particles.

2- Chemical reaction networks and their assembly in spatial arrays

Context : Living organisms perform and control complex behaviours by using webs of chemical reactions organized in precise networks. This powerful system concept, which is at the very core of biology, has seldom penetrated the field of chemistry. However, a shift from isolated reactions to supra-reactionnal chemistry (also sometime called system chemistry) would open a completely new array of applications:

The possibility to do information processing (or computation) within molecular systems

Autonomous molecular robotics

models to help our understanding of biological reaction networks.

However, it is still extremely difficult to rationally create such network architectures in artificial, in vitro settings. Our goal is to introduce a method for such a purpose, based on in vitro DNA biochemistry.

We have initially demonstrated this approach by assembling de novo an efficient chemical oscillator: we encode the wiring of the corresponding network in the sequence of small DNA templates, and obtain the predicted dynamics. This show that the rational cascading of standard elements opens the possibility to implement complex behaviours in vitro. Because of the simple and well-controlled environment, the corresponding chemical network is easily amenable to quantitative mathematical analysis. .

Results : In our recent papers:

We describe a new framework to rationally build complex reaction networks, reminiscent of those controlling living organisms, (or built by synthetic biologists), but in vitro. As a proof of concept we present the de novo assembly of a DNA oscillator (MSB 2011) or switchable chemicla memories (PNAS 2012) or the first predator-prey oscillating system (ACSnano 2013). This last system work in a closed environement and has a remarkable efficiency (up to 100 cycles)

We take advantage of the relative simplicity of the involved biochemistry to introduce chemically realistic kinetic models, which are fed with independently measured rate constants to yield quantitative predictions. This also stand in contrasts to prior works, both in vivo and in vitro, which uses mostly empirical mathematical modeling.

We also develop methods for the building and observation of non-trivial reaction networks. For example, simple and efficient fluorescent monitoring (NAR 2012), droplet-based observation of oscillations (submitted).

We have recently expanded this work to the construction of reaction diffusion systems. For example, we have observed travelling waves in the molecular predator-prey system.

We also look for the best architectures for the building of molecular systems with complex behaviors. We have proposed the use of competition as a potent non-linear primitive (submitted) for pattern classification. By comparing in vitro and in vivo system we also try to infer the design rules underlying biological information processing (PRL 2012 & PRL 2012)